Sensing system and method

ABSTRACT

A sensing method, including: emitting a signal beam; sampling the reflected signal at a sensor with a field of view larger than the signal beam; and determining a surface parameter based on the bright and dark regions associated with the sampled signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No.15/817,486, filed 20 Nov. 2017, which claims the benefit of U.S.Provisional Application No. 62/424,308 filed 18 Nov. 2016, both of whichare incorporated in their entirety by this reference.

TECHNICAL FIELD

This invention relates generally to the navigation field, and morespecifically to a new and useful time-of-flight system and method in thenavigation field.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a schematic representation of a variation of the sensingsystem in operation.

FIG. 2 is a schematic representation of the sensing system emitting asignal beam.

FIG. 3 is a schematic representation of the method of sensing systemoperation.

FIG. 4 is a schematic representation of the sensing system emitting avariant of the signal beam.

FIG. 5 is a schematic representation of the sensing system operatingbetween a first and second mode.

FIG. 6 is a specific example of an imaging optics—detector sensorarrangement

FIG. 7 is a specific example of pixels associated with a main beam,first auxiliary beam, and second auxiliary beam.

FIG. 8 is an example of the beam and the corresponding expected brightand dark pixel regions.

FIG. 9 is an example of determining the per-pixel distance of a scenesurface.

FIG. 10 is a variation of a map associating pixel indices with azimuthaland/or polar angles.

FIG. 11 is an example of a pixel-to-azimuthal angle map.

FIG. 12 is a specific example of the sensing system in use.

FIG. 13 is an example of determining external surface parameters basedon pixel signals.

FIG. 14 is an example of detecting multipath errors and/or transparentobjects based on errant pixels.

FIG. 15 is an example of detecting transparent objects based on errantpixels.

FIG. 16 is an example of sequentially generating a map of a monitoredvolume.

FIG. 17 is an example of sequentially generating a map of an ambientenvironment.

FIG. 18 is a schematic example of plane terrain determination.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of the preferred embodiments of the inventionis not intended to limit the invention to these preferred embodiments,but rather to enable any person skilled in the art to make and use thisinvention.

1. Overview.

As shown in FIG. 2, the sensing system 10o includes an emitter system200 and a detection system 300, and can optionally include a processingsystem 400, a communication system 500, auxiliary sensors 600, asecondary rangefinder, or any other suitable component. As shown in FIG.2, the sensing system functions to characterize a monitored region 20 ofthe ambient environment by resolving distances of ambient environmentsurfaces from the system (e.g., from sampled signals) and/or detect thepresence of an object proximate to the system (e.g., within range of theemitted beam 10). In one variation, the sensing system functions as anamplitude-modulated phase-offset time-of-flight system that detects theper-pixel distance of a diffusely reflective surface within the ambientenvironment.

As shown in FIG. 3, the sensing method includes: emitting a signal beamS100; sampling the reflected signal at a sensor S200; and determining asurface parameter based on the sampled signal S300. The method functionsto characterize the ambient environment. However, the method can enableany other suitable functionality.

In a first variation, the method can include: illuminating an ambientenvironment with a light beam (e.g., light sheet, cone, etc.), the beamor sheet having a minor dimension; sampling the reflected light beam ata sensor with a field of view larger than the minor dimension;determining pixel parameters for a set of pixels (e.g., bright pixels);determining a range (e.g., external surface range, object range) foreach pixel based on the pixel parameters (e.g., based on the phase shiftbetween transmission and receipt); assigning the range to apredetermined angular scene position associated with the respectivepixel; and determining ambient environment features based on the rangefor each angular scene position (e.g., generating a virtualrepresentation of the physical scene, such as a point cloud, andanalyzing the virtual representation for scene features associated withobjects or voids). This variation can optionally include detectingerrant illuminated regions within the expected dark scene, andselectively ignoring the associated pixels or virtual representations,determining transparent object parameters from the errant bright pixels,or otherwise managing the errant illuminated regions. The errantilluminated region can be: illuminated regions (e.g., regions associatedwith surface parameters determined from the returned signal) within thevirtual scene representation that are associated with an expectednon-illuminated scene region, regions with errant range readings (e.g.,ranges exceeding a threshold range, ranges outside of an expected set ofrange values, etc.), regions associated with pixels having an angularposition associated with an expected non-illuminated scene region, orotherwise determined.

In a second variation, the method can include: illuminating an ambientenvironment with a light beam or sheet, the beam or sheet having a minordimension; sampling the reflected light beam at a sensor with a field ofview larger than the minor dimension, wherein the sensor is associatedwith an expected bright region and an expected dark region; determiningpixel parameters for bright pixels within the expected bright region;and determining ambient environment features based on the pixelparameters. This variation can optionally include detecting errantbright pixels within the expected dark region, and determiningtransparent object parameters from the errant bright pixels. Thisvariation can function to characterize the ambient environment, identifyand characterize transparent objects in the ambient environment, correctfor errors in the sampled signals (e.g., multipath errors), or performother functionalities.

In a third variation, the method can include: shaping a source lighthaving a predetermined photon budget into a main light beam,illuminating the ambient environment with the main light beam, samplingthe reflected main light, and determining ambient environment featuresfor a first region corresponding to the main light beam based on thesampled reflected light. This variant can function to increase thesystem's irradiance within a monitored region, which can result in ahigher signal strength and/or higher SNR.

This variant can optionally include splitting the source light into themain light beam and an auxiliary light beam; illuminating the ambientenvironment with the main light beam and auxiliary light beam, whereinthe auxiliary light beam illuminates a second region of the ambientenvironment physically separated from the region illuminated by the mainlight beam; sampling the reflected auxiliary light in addition to thereflected main light, and determining ambient environment features forthe second region based on the sampled auxiliary light. This variant canfunction to monitor multiple regions within the ambient environment.

The sensing system and/or method are preferably used in indoornavigation and/or obstacle avoidance applications, such as consumerrobotic navigation or warehouse robotic navigation, but can optionallybe used in external navigation and/or obstacle avoidance applications,such as autonomous vehicle navigation, flight control, or otherapplications.

2. Benefits

Variants of the sensing system can confer several benefits overconventional time-of-flight systems.

First, because the field of view of the imaging system is larger than adimension of the beam, the expected resultant image encompasses bothbright and dark regions, wherein the regions can be scene regions orimage regions. These dark regions enable the system to detect andminimize multipathing effects, to detect transparent, reflective objectssuch as glass, and to perform in-situ (in-field), automatic calibrationof the sensing system and/or secondary rangefinder systems.

In a first example, errant light due to multipathing appears as faintlyilluminated pixels in an expected dark region (e.g., non-illuminatedscene region, image region, sensor region), which can subsequently beidentified and compensated for when determining the object distance fromthe system.

In a second example (shown in FIG. 13), transparent objects can beidentified in response to detection of bright pixel shift relative to anexpected bright pixel band or in response to detection of a group ofbright pixels in an expected dark pixel region (e.g., for a beam emittedat an angle to an emitter normal vector).

In a third example, the object distance as determined by a secondaryrangefinder (e.g., triangulation system or LIDAR) can be used tocalibrate the sensing system. This can function to calibrate the sensingsystem for multipath effects or other effects.

In a fourth example, the object distance as determined by the sensingsystem can be used to calibrate the secondary rangefinder (e.g.,triangulation system, such as RP-LIDAR).

In a fifth example, the sensing system can be corrected or disambiguatedbased on the position of the bright-dark pixel border in parallax shift.

However, the large image sensor field of view relative to the emittedbeam can confer any other suitable set of benefits.

Second, the system can increase the strength of the measured signaland/or increase the signal to noise ratio (SNR) by concentrating theemitted light into a narrow beam or sheet. This can further increasedetection sensitivity and/or resolution. Conventionally, the totalamount of energy that can be emitted is regulatorily limited, whichlimits the amount of light output at the emitter surface, particularlyfor wavelengths that can be absorbed by the eye (e.g., between 310 nm to1,000 nm). In conventional time-of-flight systems, this photon budgetmust be spread across the entire scene, leading to low irradiance and alower overall signal (and/or lower SNR). Here, the inventors havediscovered that for navigation and obstacle avoidance purposes,knowledge of a cross section of the scene is sufficient (e.g., a scenesection intersecting a system traversal path); in other words, theentire scene does not have to be illuminated. By shaping the previouslydisperse light into a narrow beam or sheet, the inventors are able touse the same photon budget (e.g., the same amount of emitted photons)concentrated in a smaller band. This increased photon budgetconcentration can result in higher irradiance, higher signal strength,and/or higher SNR. Additionally, or alternatively, this increased photonbudget can decrease the light emission duration, which can enable higherlight intensities to be used.

Third, the imaging system can include optics that are more suitable forcollecting the returned signal than traditional imaging optics.Conventionally, time-of-flight systems that employ light as a signal useradially symmetric imaging optics. With a shaped illumination, theoptics need not capture the entire field; this allows the regions ofinterest to be spread across the sensor more evenly and completely,increasing SNR, decreasing saturation risk, and reducing or eliminatingpoor or uneven signal returns due to lens vignetting.

However, variants of the sensing system and method can confer any othersuitable set of benefits over conventional systems.

3. Sensing System.

The sensing system is preferably mounted to a host system 700, such as arobot or vehicle (example shown in FIG. 12), but can be incorporatedinto any other suitable system or used as an independent module. Thesensing system preferably performs all or parts of the method discussedbelow, but can additionally or alternatively perform any other suitablefunction. In variations, the sensing system can operate as a modulatedtime-of-flight system (e.g., including modulated light sources withphase detectors), a range gated imager, a direct TOF imager, or anyother suitable ranging system.

The sensing system can provide data (e.g., ambient environmentparameters, obstacle parameters, etc.) to the host system for use inroute planning, object identification, object tracking, environmentmapping, environment monitoring, or any other suitable application. Thesensing system output is preferably fed to the host system processingsystem, which determines host system location based on the sensingsystem output using SLAM, particle filters, or other localizationmethods. The host system location can be used for navigation using RRTs,grid-based planning, kinematics, or other navigation methods, but can beotherwise used. The host system can additionally or alternatively usesensing system outputs to build maps of the volume (e.g., as the hostsystem traverses through the volume) or use the outputs in any othersuitable manner. The sensing system can additionally or alternativelyuse outputs from the host system components, such as outputs from theauxiliary sensors or drivetrain and/or share components with the hostsystem, such as the processing system or auxiliary sensors. In oneexample, the sensing system can use the host system pitch, as determinedfrom the host system IMU, to determine the angle of the floor for floorterrain mapping (e.g., for point cloud transform generation, point cloudplane fitting). In a second example, the sensing system can user thehost system kinematics to determine or validate the sensing system'slocation within the physical space. However, the sensing system can beseparate from or otherwise incorporated into the host system.

The system operation parameters (e.g., emission and/or sampling rate,emission intensity, sensor sensitivity, etc.) can be predetermined, varyas a function of host system kinematics (e.g., increase with increasedacceleration and/or velocity), vary based on the output's use orapplication (e.g., wherein the host system or other control systemselects a sensing system operation mode), or otherwise determined. Forexample, all or most of the emitted signal can be used to form a singlebeam for mapping purposes (e.g., to increase signal strength andminimize noise), while the emitted signal can be split into multiplebeams for obstacle detection and navigation purposes (e.g., to increasethe size of the monitored region); examples shown in FIG. 5. However,the system can be otherwise controlled.

The host system is preferably mobile and capable of traversing through aphysical space (e.g., the ambient environment), but can alternatively bestatic. The host system mobility can be limited (e.g., be terrestrialand limited to movement in two axes), be unlimited (e.g., capable ofmoving along all axes and rotations), or be capable of any suitablemotion. Examples of host systems include robots, terrestrial vehicles,aerial vehicles, aquatic vehicles, security systems, or any othersuitable host system. In a specific example, the sensing system can bemounted to and used as a safety curtain for industrial robots (e.g., asa sensing system located on an industrial robot arm). However, thesensing system can be otherwise used.

The host system can include: a processing system configured to controlhost system operation, a communications system configured to send andreceive data (e.g., short-range, such as BLE or NFC; long-range, such asWiFi or cellular; or wired, such as USB or Ethernet; etc.), a drivetrainconfigured to move the host system within a physical volume, auxiliarysensors configured to augment or supplement host system navigation(e.g., orientation sensors such as accelerometers, gyroscopes, IMUs,magnetometers; optical sensors such as cameras; motor encoders; acousticsensors such as microphones; range-finding transducers, such astriangulation systems; additional emitter-detection systems; etc.), orany other suitable component.

The sensing system is preferably configured to illuminate a medial scenesegment (e.g., portion of the scene substantially aligned with orproximal a host system midline), can alternatively or additionallyilluminate a superior or inferior scene segment (e.g., portion of thescene substantially aligned with or proximal a host system top orbottom, respectively), a right or left scene segment, or any othersuitable scene segment. The illuminated scene segment 30 is preferablyalong the direction of host travel, but can be otherwise arranged. Theilluminated scene segment can be aligned perpendicular a limited motionaxis, but can be aligned parallel the limited motion axis or otherwisearranged. For example, the illuminated scene segment can be a horizontalsegment when the host system is a terrestrial system (e.g., limited tomotion in the x-y plane). However, the illuminated scene segment can beotherwise configured.

The sensing system is preferably mounted to a medial section of the hostsystem (e.g., proximal a midline or geometric center of the hostsystem), but can alternatively be mounted to a superior portion,inferior portion, a right or left side, or any other suitable portion ofthe host section. The sensing system is preferably mounted such that thebeam is emitted at an angle (e.g., 0°, 45°, 90°, etc.) relative to areference plane, wherein the reference plane can be a host systemtransverse plane, sagittal plane, or coronal plane, a ground plane, aceiling plane, or any other suitable plane. The angle can bepredetermined (e.g., based on the host system dimensions, such as heightand width), dynamically adjusted (e.g., based on host system pitch, yaw,roll, height, etc.), or otherwise determined. Additionally, oralternatively, the sensing system is mounted such that an active surfaceof the detection system is substantially parallel the illuminated scenesegment. However, the sensing system can be mounted in any othersuitable configuration.

Each host system can include one or more sensing systems, whereinmultiple sensing systems are preferably mounted to the host system suchthat the scenes (regions) monitored by each sensing system does notoverlap. However, the multiple sensing systems can be mounted such thatthe monitored regions overlap, or be otherwise mounted.

As shown in FIG. 1, the sensing system 100 can include an emitter system200 and a detector system 300.

a. Emitter System.

As shown in FIG. 1, the emitter system 200 of the sensing system 100functions to emit a signal beam 10, which strikes a scene. The emittersystem is preferably controlled by the control system (e.g., processingsystem) and powered by an on-board power supply of the sensing system orhost system (e.g., rechargeable battery, solar system, thermionicsystem, etc.), but can be otherwise controlled or powered.

The beam 10 (and/or underlying signal) is preferably light, but canalternatively be electromagnetic signals (e.g., radio waves), acousticsignals, or be any other suitable signal. The signal is preferablyemitted from the emitter system as a beam or sheet (sheet of light,light sheet), but can additionally or alternatively be divergent,disperse, structured, patterned, or have any other suitable form factoror geometry. The beam emitted by the emitter system is preferablycharacterized by a set of beam parameters, which can include beamcross-section (e.g., perpendicular the emission vector, parallel theemission vector, etc.), beam dimension, beam intensity, beam divergence,beam shape, beam quality, beam astigmatism, beam jitter, lightwavelength(s), light phase, beam orientation, or any other suitableparameter.

The beam can have a single wavelength or a range of wavelengths. In onevariation, the light forming the beam is preferably IR light, morepreferably near-IR light (e.g., between 700 nm to 3,000 nm) butalternatively mid-infrared (between 3,000 nm to 50,000 nm) orfar-infrared (50μ-1,000μ); but can alternatively be visible light, UVlight, or have any other suitable wavelength (or range thereof) withinthe electromagnetic spectrum. In one embodiment, the beam has awavelength of 850 nm. The beam wavelengths emitted by the emitter systemcan remain constant over time (e.g., be a predetermined wavelength set),vary over time (e.g., vary between sequential pulses), or be otherwisedetermined. The beam intensity emitted by the emitter system (e.g.,post-shaping), is preferably lower than or substantially equal to theregulatory limits, but can alternatively be higher.

The beam emitted by the emitter system is preferablyamplitude-modulated, but can be otherwise modulated (e.g., phasemodulated, frequency modulated, polarization modulated), unmodulated, orhave any other suitable structure. The beam can be directly modulated(e.g., by modulating the current driving the light source, such as withan RF modulator), externally modulated (e.g., by a light modulator, adiffractive or refractive film at the light exit), or otherwisemodulated by an optical modulator. The modulator can be an absorptivemodulator, refractive modulator (e.g., electro-optic modulator,acousto-optic modulator, etc.), a refractive modulator connected to aninterferometer or directional coupler, or any other suitable modulator.In one variation, the signal emitted by the emitters (e.g., sourcesignal, source light) can be modulated (e.g., at a frequency between 1kHz-100 kHz or any other suitable frequency), wherein the beam is formedfrom the modulated raw signal. In a second variation, the signal emittedby the emitters can be unmodulated, wherein the signal shaper modulatesthe signal during beam shaping. Alternatively, the beam can be modulatedby a light modulator after shaping. However, the beam can be otherwisemodulated or adjusted.

The emitter system can emit beams with one or more modulationfrequencies, wherein different frequencies can be used to validate orrefine the object detection output. For example, beams with a secondfrequency can be used to heterodyne longer ranges (e.g., with higherconfidence and/or resolution), and beams with a third frequency can beused to aid disambiguation. However, the different frequencies can beused in any other suitable manner. Beams with different frequencies arepreferably emitted and sampled asynchronously (e.g., serially, accordingto a schedule, etc.), but can alternatively or additionally be emittedand/or sampled concurrently.

The beam is preferably oriented parallel to the normal vector ofdetecting sensor active surface, but can additionally or alternativelybe oriented perpendicular to a vertical axis of the host system,perpendicular to a gravity vector (e.g., wherein the emitter or sensingsystem can be mounted on a gimbal or other rotational system, staticallymounted to the host system, etc.), parallel to a host system supportsurface, or be oriented at any other suitable angle.

The beam can be divergent, diffused, substantially collimated (e.g.,with little or no divergence), or have any other suitable divergence orparameter value.

As shown in FIG. 1, the beam is preferably a sheet with an elliptical,rectangular, or other cross section, but can optionally have a circularcross section or any other suitable cross section. The beam crosssection can have a major dimension (e.g., extending along a main axis ormonitoring axis of the scene) and a minor dimension (e.g., extendingalong a minor axis or auxiliary axis of the scene), example shown inFIG. 8, or have any suitable set of dimensions. One or more beamdimensions (e.g., beam width, beam height, beam diameter, etc.) ispreferably smaller than the imaging sensor's (and/or resultant image's)field of view (FOV) or active area (e.g., less than 10%, 20%, 50%, orany other suitable proportion of the FOV or active area), but the beamcan alternatively have one or more dimensions equal to or larger thanany other suitable set of FOV dimensions. In one example, the minordimension is smaller than the corresponding dimension (e.g., paralleldimension) of the imaging sensor or image FOV. In a specific example,the minor dimension can be the beam height, wherein the imaging sensorFOV (and resultant image's FOV) height is larger than the beam (e.g.,extends above and/or below the beam). In this example, the majordimension can be smaller than, equal to, or larger than thecorresponding dimension of the imaging sensor FOV. However, the beamdimensions can be otherwise related to the imaging sensor and/or imageFOV.

In variants where the beam has a non-circular cross section, the beam ispreferably oriented with the main axis extending horizontally (e.g.,substantially perpendicular to the host system vertical axis or gravityvector; substantially parallel to the support surface, etc.), but canalternatively be oriented with the main axis extending vertically or atany other suitable angle. In these variants, the beam diameter along theminor axis is preferably smaller than the field of view of the imagingsensor in the corresponding dimension (e.g., the beam height is smallerthan the FOV height), while the beam diameter along the major axis canbe less than, equal to, or larger than the field of view of the imagingsensor in the corresponding dimension (e.g., the beam width is largerthan the FOV width). In these variants, the beam diameter and/ordiameter resulting from divergence along the major axis is preferablylarger than the host system in the corresponding dimension (e.g., widerthan the robot width), but can be smaller than, equal to, or otherwisedimensioned relative to the host system dimensions.

The emitter system 200 can include an emitter 220 (e.g., an illuminationunit), signal shaper 240 (e.g., emitter optics), and/or any othersuitable set of components. The sensing system preferably includes asingle emitter system, but can alternatively include multiple emittersystems. In the latter instance, the emitter systems preferablyilluminate separate and distinct (e.g., non-overlapping) physicalregions, but can alternatively illuminate the same physical region(e.g., wherein the emitted signal can be directed toward the samephysical region, be shaped into a common beam, etc.). The emitter systemand components thereof are preferably statically mounted to the sensingsystem (e.g., sensing system housing, host system housing) and/ordetection system (e.g., by the sensing system housing), but canalternatively be actuatable (e.g., mounted to a motor or otherpositioning system) or otherwise mounted.

The emitter 220 of the emitter system 200 functions to emit the signalthat subsequently forms the beam. The signal is preferably light, butcan alternatively be electromagnetic signals (e.g., radio waves),acoustic signals, or be any other suitable signal. The signal can havethe same parameters as the beam (e.g., dimensions, intensity,divergence, modulation frequency, etc.) or have different parametersfrom the beam. The signal emitted by the emitter preferably has the beamwavelength, but can alternatively have any other suitable wavelength.The signal can be pulsed light, a continuous wave, a quasi-continuouswave, or otherwise structured. However, any other suitable signal can beemitted. The emitter system can be a point source, line source, or anyother suitable source.

The signal intensity emitted by each individual emitter and/or emitterset (e.g., source light, pre-shaping) is preferably lower than orsubstantially equal to the limit prescribed by regulatory standards(e.g., according to IEC-62471, IEC-60825, or any other suitablestandard), such that the optical detection system has a limited photonbudget, but the signal intensity can alternatively be higher. The signalcan be emitted with an optical power output equal to, less than, orgreater than: 10 mW, 500 mW, 2 W, any power output therebetween (e.g.,40-100 mW), or any other suitable power output limit. In a specificexample, the emitter can be a 2 W VCSEL array The emitter can beconstantly on, pulsed at a predetermined frequency, or otherwiseoperated. However, the signal can be emitted at power levels above theregulatory emission limit, or at any other suitable power level.

The emitter system can include one or more emitters, wherein multipleemitters can be arranged in an array or otherwise arranged. The emitterscan include one or more signal-emitting elements, such as illuminationunits (light-emitting elements, luminaires,), radios (e.g., Bluetooth,WiFi, other electromagnetic wave-emitting element, etc.), acoustic units(e.g., speakers), or any other suitable signal-emitting element. Theillumination unit can be a laser, LED, OLED, incandescent light, or anyother suitable light-emitting element. The emitter can be an IEC-60825Class 1, 1M, 2, 2M, 3, 3B, or 4 emitter, be any other suitableregulatory-compliant emitter, or be any other suitable emitter.Alternatively, the emitter can emit light at any suitable emissionlevel, which can be statically set or dynamically change (e.g., based onoperating context, such as whether a user is proximal the system).

The signal shaper 240 of the emitter system 200 functions to form thebeam. The signal shaper can optionally change the emitted signalparameters. The signal shaper is preferably statically mounted relativeto the emitter (e.g., a predetermined distance away from the emitter),but can alternatively be actuatably mounted or otherwise mounted. Theemitter system can include zero, one, or multiple signal shapers. Eachemitter can be paired with one or more signal shapers. However, theemitters and signal shapers can be otherwise configured.

In a first variation as shown in FIG. 2, the emitter optics can includefocusing optics, which function to focus the light into a beam havingthe desired parameters. Focusing optics that can be used can include:apertures, lenses (e.g., optical collimating lens, etc.), mirrors (e.g.,an optical cavity with parallel mirrors; concave mirrors, flat mirrors,parabolic mirrors, spherical mirrors, etc.), freeform molded optics, orany other suitable focusing system.

In a second variation, the emitter optics can include a beam shaper 242,which functions to shape the light incident on the scene. Beam shapersthat can be used include: apertures, field mappers, beam integrators,lenses, mirrors, diffusers, diffractive elements, prisms, or any othersuitable beam shaping system. The beam shaper can be made of glass(e.g., transparent material), specular reflective material (e.g.,mirrored surfaces), or any other suitable material. However, any othersuitable beam shaper can be used.

In a third variation, the emitter optics can include splitting optics,which functions to split the light into multiple beams. In a firstembodiment, the splitting optics can focus or shape light from multipleemitters into a predetermined number of beams. In a second embodiment,the splitting optics can split a single beam into multiple beams.However, the splitting optics can function in any other suitable manner.When the splitting optics is used with other emitter optics, thesplitting optics can be arranged between the emitter and the focusingoptics, arranged distal the emitter downstream from the focusing optics,or be arranged in any other suitable position. However, the same systemcan function as both splitting optics and focusing optics, or performany other suitable functionality. The splitting optics can include:multiple apertures, prisms, mirrors (e.g., angled mirrors), diffractiveelements, freeform optics, engineered diffuser surfaces, or any otheroptics capable of creating multiple beams.

The resultant beams are preferably separated from each other (e.g., onthe incident scene) by an emission angle, but can alternatively becontiguous or otherwise arranged. The resultant beams are preferablyseparated from each other by a separation angle (e.g., at emission), butcan alternatively be separated by a separation distance or otherwiserelated. For example, the resultant beams can be 10° apart, 30° apart,45° apart, or separated by any other suitable separation angle. In aspecific example, a downward-facing beam is directed at a downward angleof 31°. The separation angle can be predetermined (e.g., based on theheight of the primary system, the sensing system placement on theprimary system, the number of beams, the total monitored scene region,etc.), dynamically determined (e.g., based on the location of anidentified scanning region relative to the sensing system mountingpoint, etc.), or otherwise determined. The separation angles can beequal or different. The separation angle is preferably defined along thebeam minor axis (e.g., scene auxiliary axis), but can alternatively bedefined along the beam major axis (e.g., scene monitoring axis) or alongany other suitable axis. The separation angle can be an altitude, anazimuth, or be any other suitable angle extending along any othersuitable plane. The separation angle can be measured from the beam majoraxis, beam minor axis, or relative to any other suitable portion of thebeam. The resultant beams are preferably at a predetermined emissionangle relative to each other, but can alternatively or additionally beparallel to each other, illuminate parallel scene segments, beperpendicular (or at any suitable angle, such as 30°, 60°, or arrangedin any other suitable relative orientation.

The resultant beams can have the same intensity (e.g., same irradiance,same number of photons, etc.) or different intensities. For example, theemitter optics can split the source signal (e.g., source light) into afirst beam with 10% of the photon budget and a second beam with 90% ofthe photon budget. The relative intensities between the beams can bepredetermined, dynamically determined (e.g., based on obstacles detectedin prior samples, ambient light in each monitored scene segment, etc.),or otherwise determined.

In one example, the splitting optics split the emitted beam into a mainbeam with 80% of the light, and two auxiliary beams, each with 10% ofthe light and separated from the main beam by a first and secondpredetermined angle, respectively (e.g., 30° and 20°, respectively; both30°; etc.). The main beam and auxiliary beams are preferably separatedvertically (e.g., perpendicular to the main beam major axis), such thatthe uppermost auxiliary beam (high beam, clothesline beam) is directedupwards and the lowermost auxiliary beam (low beam, floor beam) isdirected downwards, but can be otherwise aligned. In a specific example,the low beam intersects a plane perpendicular to the primary systemvertical plane and/or parallel to the primary surface support surface(floor plane or cliff plane) within a predetermined distance of theemitter system or primary system housing (e.g., within 1 inch, 6 inches,1 foot, etc.), while the high beam intersects a top plane (“clothesline”plane), parallel to the floor plane, intersecting the primary systemtop, or otherwise defined, within a second predetermined distance of theemitter system or primary system housing (e.g., within 1 inch, 6 inches,1 foot, etc.). However, the beams can be otherwise oriented.

b. Detection System.

The detection system 300 of the sensing system 100 functions to samplesignals emitted by the emitter system and returned (e.g., reflected) bysurfaces in the environment surrounding the sensing system. Thedetection system can sample a representation of the returned signal 40,which can be an image or any other suitable representation. Thedetection system is preferably controlled by the control system andpowered by the same power supply as the emitter system, but can beotherwise controlled and/or powered.

The sensing system can include one or more detection systems. In onevariation, the sensing system includes a single detection system for allbeams emitted by the emitter system(s). In a second variation, thesensing system includes a detection system for each beam. In a thirdvariation, the sensing system includes multiple detection systems for abeam. However, the sensing system can include any suitable number ofdetection systems. The detection system is preferably arranged proximateto the respective beams' emitter system (e.g., above, below, to theside, etc.; coplanar, recessed, proud, etc.), but can be otherwisearranged (e.g., wherein the recorded image is reflected or otherwiseredirected to the detection system). The detection system is preferablyarranged along the minor axis of the beam relative to the emittersystem, but can be otherwise arranged. The detection system ispreferably statically coupled to the emitter system, but can beactuatably coupled or otherwise coupled to the emitter system. Thedetection system is preferably arranged such that the detector activeface is parallel to and codirectional with the emitter active face, butcan be arranged at a non-zero angle to the emitter active face orotherwise arranged.

The detection system preferably outputs signal representations (e.g.,images) of the scene illuminated by the signal (illuminated scene), butcan alternatively or additionally generate a set of pixel signalsindicative of signal reflections off the scene surfaces, or sample anyother suitable set of data. The images can be visual images, acousticimages (e.g., spatial representation of sound), electromagnetic images,or any other suitable image. The detection system is preferablyconfigured to cover (e.g., monitor, capture, sample) a broader region ofthe scene than the beam emitted by the emitter system, but canalternatively cover the same region, a region of similar size, a smallerregion, or any other suitable region relative to the region covered bythe emitter system (e.g., region illuminated by the emitter system). Inone variation, detection system preferably has a detection area or fieldof view (FOV) larger than a dimension of the signal beam, but canadditionally or alternatively have a FOV larger than a dimension of thesegment of the scene illuminated by the emitter system (illuminatedscene), or have any other suitable FOV. The resultant image preferablyhas a FOV (e.g., scene portion that the image represents or captures)with one or more dimensions larger than the beam, but can alternativelyhave a FOV with any other suitable set of dimensions. The resultantimage can have the same FOV as the sensor, be cropped, or be otherwiserelated to the sensor FOV.

The detection system is preferably configured such that the expectedresultant image includes both bright pixels 42, corresponding to signalsreflected by the illuminated scene and received at the detector sensor,and dark pixels 44, corresponding to the non-illuminated regions of theenvironment. In this variation, the image and/or sensor can beassociated with an expected bright region (including a set of expectedbright pixels or expected illuminated scene regions) for each beam thatcorresponds to the respective illuminated scene (and/or sensor regionexpected to receive the respective beam reflection), and expected darkregion(s) (including set(s) of expected dark pixels) that correspond tothe non-illuminated scene (and/or sensor region(s) expected to receivelittle to no beam reflections).

The expected bright region is preferably associated with a predeterminedpattern, predetermined virtual region within the virtual scenerepresentation, predetermined set of positions relative to a host system(e.g., based on system pose relative to the host system; illuminatedregions in global coordinates; etc.), or any other suitable parameter.The predetermined pattern is preferably dependent upon the beamparameters (e.g., preferably substantially similar to the beamparameters or be a scaled version thereof), but can be otherwisedetermined. For example, a band can be expected in the resultant imagewhen the light beam is formed into a sheet, while a diffuse pattern canbe expected when the beam path includes a diffuser.

In a first specific example wherein the emitter system emits ahorizontal light sheet and the detection system samples a region tallerthan the illuminated scene section, the image can be associated with anexpected bright band, corresponding to the illuminated scene section andan upper and lower expected dark band corresponding to non-illuminatedscene sections. In a second specific example, wherein the emitter systememits an upper, middle, and lower horizontal light sheet and thedetection system samples a region taller than the monitored regionextending between the upper and lower illuminated scenes, the image canbe associated with an upper, middle, and lower expected bright bandcorresponding to the upper, middle, and lower illuminated scenesections, and intervening dark bands corresponding to non-illuminatedscene sections. The bright bands can include non-contiguous orcontiguous bright pixels, wherein the bright pixel arrangement, density,or other parameters can be determined based on the band pair separationdistance, emission angle, emission intensity, or otherwise determined.

However, the reflected signal can be otherwise represented in the image.However, the detection system can be otherwise dimensioned and theresultant image can include any other suitable distribution of brightand dark pixels. However, the detection system can be otherwiseconfigured.

The detection system 300 can include one or more detector sensors 320,signal collectors 340, or any other suitable component.

The detector sensor 320 of the detection system 300 functions to samplethe reflected beam (e.g., signals of the beam reflected off surfaces ofthe ambient environment). The detector sensor can sample the beamintensity or amplitude, phase, angle of arrival, or any suitable signalparameter. The detector sensor is preferably an image sensor, but canalternatively or additionally be an optical sensor, an acoustic sensor,electromagnetic sensor (e.g., radio), or be any other suitable sensor.The detector sensor is preferably sensitive in the sensor wavelengths(e.g., be an IR sensor), but can alternatively be sensitive to a wideror narrower range of wavelengths. The image sensor can include one ormore CCD sensors, CMOS sensors, photodetector arrays, or any othersuitable imaging system. The image sensor can optionally include ashutter (e.g., operate similar to a range gated imager), optical gate,or any other suitable component. Alternatively, or additionally, thedetector sensor can be an optical receiver (e.g., IR receiver), phasedetector, or be any other suitable sensor. The detector sensor can be aone, two, or multiple directional sensor. The detector sensorsensitivity is preferably predetermined and static, but canalternatively be dynamically adjusted (e.g., based on ambient light ornoise, operating context, power source SOC, detected or anticipatedexternal obstacles, etc.) or otherwise determined. The sample (e.g.,image) sampled by the detector sensor can have a crop factor of 1, lessthan 1, more than 1, or be otherwise related to the sensor active area.

The detector sensor preferably includes an array of sensing elements(e.g., pixels), but can be otherwise configured. The pixels of thedetector sensor and/or resultant image are preferably individuallyindexed, but can be otherwise identified. The pixel position within thedetector sensor is preferably associated with a physical position in themonitored scene. In one variation, different pixel sets arranged along asensor axis can be assigned to different angular positions relative tothe sensing system (e.g., within a plane shared by the axis and thesensing system). In one embodiment, each pixel is assigned (e.g.,mapped) to a predetermined azimuthal angle and/or polar angle relativeto the sensing system (examples shown in FIG. 10 and FIG. 11), which canbe converted to a host system coordinate system based on a predeterminedmapping between the sensing system and host system (e.g., based on thesensing system's mounting location and angle relative to a host systemreference point) and/or global coordinate system based on the hostsystem global location and pose (e.g., determined from host systemlocation sensors, range-finding systems, pose sensors, etc.). Forexample, each pixel within a horizontal expected bright band (e.g.,extending along a monitoring axis) can be associated with a differenthorizontal angular position (azimuthal angle; φ) relative to the sensingsystem (e.g., increasing from −90° to 90° going from leftmost pixels torightmost pixels along the monitoring axis). In another example, eachpixel along a vertical axis is associated with a different altitude orvertical angular position (polar angle; θ) relative to the sensingsystem. The physical position associated with each pixel is preferablypredetermined (e.g., through calibration), but can alternatively bedynamically determined (e.g., through real-time calibration using asecond range-finding system, IMU output, consistent bright band shift,etc.) or otherwise determined. However, the pixels can be otherwiseidentified and/or correlated to the physical monitored scene.

The signal collector 340 of the detection system 300 function to focus,adjust, and/or redirect the signals from the environment to the detectorsensor. The signal collector can include imaging optics, acousticamplifiers (e.g., trumpets), filters, or any other suitable signalmodification component. The imaging optics can be centered relative tothe image sensor, positioned or formed to distort the collected returnsignal, or otherwise positioned relative to the image sensor. Theimaging optics can include lenses (e.g., wide-angle lens, ultrawide-angle lens, normal lens, long focus lens, fisheye lens, etc.),mirrors, prisms, panoramic annular lenses, freeform refractive orreflective optics, or any other suitable set of optics. The imagingoptics (e.g., lens) can be concentrically arranged with the detectorsensor, offset from the detector sensor, or otherwise arranged. In oneexample (shown in FIG. 6), the detection system includes a panoramicannular lens offset from the detector sensor (e.g., offset from thecenter of the detector sensor's active surface), wherein a center of thepanoramic annular lens is substantially aligned with (e.g., withinmanufacturing tolerances) or proximal an edge of the detector sensor,preferably the edge opposing the signal emission direction, butalternatively any suitable detector sensor edge. The panoramic annularlens can be offset such that 180°, 60°, 270°, or any suitable portion ofthe collected signal is sampled by the detector sensor. This canfunction to increase the resolution of the sampled signals, as more ofthe detector sensor's active surface (and/or resultant image) is beingused to sample the scene regions of interest.

The imaging optics preferably include a band-pass filter matched to theemitted wavelength but can alternatively include a low-pass filter, anyother filter, or no filter. The imaging optics are preferably axiallysymmetric, but can alternatively be radially symmetric, asymmetric, orhave any other suitable symmetry. The imaging optics are preferablyaxially symmetric about the monitoring axis, but can additionally oralternatively be axially symmetric along the auxiliary axis or any othersuitable axis. The imaging optics can be made of polycarbonate,polystyrene, glass, or any other suitable material. However, thedetection system can include any suitable set of imaging optics and/orsignal collectors.

In a first variation, the sensing system includes: an emitter configuredto emit a source light (e.g., illumination unit); a signal shaperincluding emitter optics optically connected to the illuminator andconfigured to shape the emitted light into a narrow beam or sheet; adetection system including an image sensor; and a signal collector(e.g., including a wide-angle lens) with a field of view larger than aminor dimension of the narrow beam or sheet, such that the expectedresultant image includes both bright pixels and dark pixels (exampleshown in FIG. 1).

In a second variation, the sensing system includes the components of thefirst variation, and additionally includes a set of splitting opticsconfigured to split the emitted beam, pre- or post-light focusing, intomultiple auxiliary beams directed in different directions (e.g.,redirect a predetermined proportion of the emitted light at apredetermined angle relative to the main beam). The image sensor canhave a field of view large enough to capture reflected light from boththe main and auxiliary beams as well as dark pixels. Alternatively, thedetection system can include multiple image sensors, each arranged andsized to capture reflected light from a main or auxiliary beam. However,the sensing system can be otherwise configured.

c. Additional Systems.

The sensing system can optionally include a control system. The controlsystem can be responsible for any or all of the system operations,including: data routing, detector initialization, emitter driving,signal processing, surface parameter determination (e.g., distancedetermination, object detection), map generation, route management(e.g., planning, control, navigation, etc.), and/or any other operation.Alternatively, the sensing system can include one or more specializedcontrol systems for each or a subset of the processes discussed herein.Alternately, any of the system components can be externally controlled,automatically controlled, or uncontrolled. The control system can bepreferably combined with the processing system but can also be separate.

The sensing system can optionally include driver electronics, whichfunction to control and synchronize emitter system and/or imaging systemoperation. The driver electronics preferably have a high clock frequency(e.g., 10 MHz to 200 MHz), but can alternatively have any other suitableclock frequency. In one variation, the driver electronics can controlthe imaging system to sample the image at the same frequency as beam orsignal emission, with or without a delay. In a second variation, thedriver electronics can control the imaging system to sample a series ofimages (e.g., with high shutter speeds, such as several hundredpicoseconds, or low shutter speeds) for each beam pulse. However, thedriver electronics can be otherwise operated.

The sensing system 100 can optionally include a processing system 400that functions to determine object parameters from the recorded signal.The processing system can optionally control sensing system operation,control sensing system communication with external components, orperform any other suitable functionality. For example, the processingsystem can function to detect the presence of an object in theilluminated scene based on the recorded image, determine the objectposition relative to the sensing system based on the recorded image,determine the object distance from the sensing system based on therecorded image, identify the object based on the recorded image, orperform any other suitable functionality.

The processing system of the sensing system can determine environmentalinformation based on the sampled signal(s). The processing system canprocess the signals in real- or near-real time, in batches, at apredetermined frequency, in response to processing event occurrence, orat any suitable time. In a first variation, the system can determineobject presence in response to: bright pixel detection in the recordedimage, returned signal detection in the recorded image, calculateddistance (from the returned signal) falling within the system'sdetection range, or otherwise determined. In a second variation, thesystem can determine the relative object position (e.g., the angularobject position relative to the sensing system) based on the location ofthe bright pixel(s), associated with the object, in the recorded image.In a third variation, the system can determine object distance from thesensing system based on phase shift between the emitted and receivedsignal, time of beam or signal emission, time of signal receipt, pixelintensity, or otherwise determine the object distance. In a fourthvariation, the system can detect transparent object presence based onerrant bright pixel detection in the dark pixel regions. In a fifthvariation, the system can determine transparent object parameters basedon the pixel parameters of the errant bright pixels. However, theprocessing system can perform any other suitable process. The processingsystem can also filter, flag, bin, combine, average, smooth, de-warp, orotherwise pre- or post-process data (e.g., sampled signals, time series,etc.). The processing system can include on-board processors (e.g., CPU,GPU, TPU, microprocessor, ASIC, etc.), host processors, remote computingsystems (e.g., auxiliary device processors, user device processors,server systems, etc.), a combination thereof (e.g., wherein raw orprocessed data is transmitted between the source system and processingsystem) or include any other suitable processor.

The sensing system 100 can optionally include a communication system500, which functions to communicate data to an endpoint. The data caninclude object parameters (e.g., presence, relative position, distance,etc.), maps (e.g., of the floor, of the clothesline plane, etc.),operation instructions, calibration instructions, sensor data, or anyother suitable information. The data can be transmitted at apredetermined frequency, at the sensor sampling frequency, in responseto occurrence of a transmission event (e.g., error detection,recalibration, etc.), passed through (e.g., in real- or near-real time),or transmitted at any other suitable time. The data can be processed orunprocessed (e.g., raw). The endpoint can be a user device, a remotecomputing system, the host system (primary system), a second primarysystem, or be any other suitable system. The data can be transmittedthrough a wired connection, wireless connection, or any other suitableconnection, using any suitable protocol. The communication system can bea wired communication system (e.g., Ethernet, vehicle data bus, etc.), awireless communication system (e.g., WiFi, cellular, Thread, Bluetooth,UWB, NFC, etc.), or any other suitable communication system.

The sensing system 10o can optionally include auxiliary sensors 600,which can function to provide sensor inputs to the driver electronicsfor imaging system and/or emitter system operation. The auxiliarysensors can optionally provide inputs to the processing system forobject parameter determination correction or modification. The auxiliarysensors can additionally or alternatively be host system sensors oranother system's sensors, wherein the sensor outputs can be fed to thesensing system. Examples of the auxiliary sensors include opticalsensors, such as ambient light sensors; orientation sensors, such asaccelerometers, gyroscopes, IMUs, magnetometers, and altimeters; audiosensors, such as microphones; ranging systems, such as auxiliary TOFsystems, LIDAR systems, or wireless signal trilateration systems; or anyother suitable sensor. In a first example, the driver electronics candynamically change the exposure time or emission power based on theambient light detected by the ambient light sensor (e.g., decrease theexposure time with increased ambient light). In a second example, theprocessing system can incorporate sensing system kinematics (e.g.,primary system kinematics) based on wheel encoders, motor powerregulators, or any other suitable sensor information. However, theauxiliary sensors can be otherwise used.

The sensing system can include one or more auxiliary rangefinders, whichfunction to augment and/or provide a reference point for sensing systemcalibration. The auxiliary rangefinder can be an active rangefinder,such as a laser rangefinder, LIDAR, radar, sonar, or ultrasonicrangefinder, a trigonometric rangefinder, such as a stadiametricrangefinder, parallax or coincidence rangefinder, or any other suitablerangefinder. The auxiliary rangefinder is preferably statically mounteda predetermined distance from the sensing system and/or components ofthe sensing system, but can be otherwise mounted. The auxiliaryrangefinder is preferably different from the sensing system (e.g.,thereby suffering from different drawbacks), but can alternatively bethe same.

The sensing system can optionally include a power system. The powersystem can supply voltage or current at any appropriate level to any ofthe system components and/or source energy from an on-board power supply(e.g., rechargeable battery, solar system, thermionic system, energyharvesting system, etc.) or an external source. Alternately, the sensingsystem can be powered externally or be unpowered.

4. Method.

As shown in FIG. 3, the method of sensing system operation can include:emitting a signal beam S100; sampling the reflected signal at a sensorS200; and determining a surface parameter based on the sampled signalS300. The method can additionally or alternatively include: identifyinga transparent, partially-reflective surface based on the sampled signalsS400; determining obstacle parameters based on the sampled signals;generating a map based on a series of sampled signals S500 (e.g.,sampled as the host system moves through a physical space); generating adistance record of the sensing system surroundings (e.g., a distancemap, vector, point cloud, etc.); generating navigation instructionsbased on the distance record; calibrating the sensing system; or anyother suitable process.

The method functions to determine the distances to external surfaceswithin the sensing system's line of sight (e.g., based on the signalreturn). The method is preferably performed in real- or near-real time(e.g., as the sensor signals are received), but can alternatively beperformed asynchronously, after a predetermined delay, or at any othersuitable time. Processes of the method are preferably performed inparallel, but can alternatively be performed sequentially or in anyother suitable order. The method is preferably performed on-board thesensing system, but can alternatively be performed on-board the primarysystem incorporating the sensing system, be performed by a remotecomputing system, or be performed by any other suitable system. Themethod is preferably performed by or using the sensing system disclosedabove, but can alternatively be performed by any other suitable system.

a. Emitting a Signal Beam

Emitting a signal beam S100 functions to emit a signal beam forsubsequent recordation and analysis. The signal beam is preferablyemitted by the emitter system, but can alternatively be emitted by anexternal system, be ambient light, or be emitted by any other suitablesignal source. The signal beam can be emitted at a predeterminedfrequency (e.g., rate), in response to sampling event occurrence (e.g.,the signal output by an auxiliary sensor satisfies a predeterminedcondition), at a time specified by a selected operation mode, at a timespecified by a control system, or at any suitable time.

Emitting the signal beam can include: emitting a source signal S120 andforming a shaped signal from the source signal S140. However, the signalbeam can be otherwise emitted.

Emitting the source signal S120 functions to emit a signal for sceneirradiance. The signal preferably has a predetermined wavelength, butcan alternatively have any suitable set of wavelengths. The signal ispreferably infrared light (e.g., 850 nm), but can alternatively be lightof any other suitable wavelength or be any other suitable signal. Thesignal can be collimated, uncollimated (e.g., divergent), or beotherwise structured. The signal can be a constant wave, aquasi-constant wave, continuous wave, a modulated signal, or be anyother suitable signal. The modulated signal can be amplitude modulated,phase modulated, frequency modulated, polarization modulated, wavelengthmodulated, or otherwise modulated. The modulation frequency can beconstant, variable, or otherwise configured. The signal is preferablyemitted by an emitter system, more preferably the emitter of an emittersystem, but can be emitted by an external system, be ambient light, orbe emitted by any other suitable signal source. The emitter systempreferably emits the signal at an emission time, which can be the timeat which the emitter emits the signal, the time at which the signalleaves the emitter optics or emitter system, or be any other suitabletime. Signal emission is preferably controlled by driver electronics(e.g., with high clock frequencies), but can alternatively be controlledby any other suitable system.

The signal is preferably emitted at or below a regulatory power limit(e.g., 1000 mW, 100 mW, 10 mW, 5 mW, etc.), but can alternatively beemitted at a higher power or at any suitable power. The signal emissionduration is preferably predetermined and substantially short (e.g., 10onanoseconds, 10 nanoseconds, etc.), but can alternatively be dynamicallyvaried based on operation context (e.g., ambient light levels, ambientenvironment complexity, etc.) or any other suitable parameter, orotherwise determined. Emitting the signal preferably includes pulsingthe signal at a predetermined frequency (e.g., emitting the signal at apredetermined frequency), at a varying frequency (e.g., dependent uponthe operating context, auxiliary sensor signals, etc.), or any othersuitable frequency. Alternatively, emitting the signal can includeconstantly emitting the signal (e.g., leaving the illumination unit on),and selectively shuttering or otherwise adjusting the emitted signal.The predetermined frequency can be manually determined, set by theemitter speed, set by the imaging system speed, determined based on thesignal speed (e.g., speed of light) and maximum monitored range, orotherwise determined. The emission frequency is preferably selected suchthat serially emitted signals do not interfere with each other (e.g.,the subsequent signal is preferably emitted after the first signal isrecorded or dissipated), but can be otherwise selected. However, thesignal can be otherwise emitted.

Forming a shaped signal from the source signal S140 functions toaggregate the photons within the photon budget into a controlledillumination region. This can function to increase the system'sirradiance capabilities for the monitored scene region. The shapedsignal is preferably a beam or sheet, more preferably a narrow beam orsheet, but can alternatively have any suitable geometry orconfiguration. The beam is preferably formed by modifying the emittedsignal into the beam, but can alternatively or additionally be formed bythe emitter (e.g., using a structured light source) or otherwise formed.The source signal is preferably shaped into the beam, but canalternatively or additionally be focused into the beam, directed intothe beam, selectively interfered with (e.g., destructive and/orconstructive) to form the beam, projected (e.g., passed through a filteror spatial light modulator), or otherwise modified to form the beam.All, a majority, more than a threshold percentage or proportion (e.g.,99%, 90%, 80%, 75%, 60%, etc.), a minority, less than the thresholdpercentage, or any suitable proportion of the emitted light ispreferably used to form into the beam(s) (example shown in FIG. 4; e.g.,one or more beams). However, portions of the emitted light can beblocked, redirected, or otherwise unused for scene illumination.

The emitted signal is preferably modified into one or more beams orsheets, oriented at predefined angles and/or positions, but canalternatively be formed into any other suitable pattern. For example,three, substantially parallel narrow beams can be formed from theemitted signal. The beam is preferably a narrow beam (e.g., a sheet),but can alternatively be a point source, a pattern (e.g., formstructured light), or have any other suitable geometry. A narrow beamcan be a beam having a minor cross-sectional axis (minor axis, auxiliaryaxis, etc.) smaller than a major cross-sectional axis (major axis,monitoring axis, etc.), a beam having a cross-sectional dimensionsmaller than an imaging sensor dimension, a beam having across-sectional dimension smaller than a predetermined value, such as 5mm or 0.1 mm, or be otherwise characterized. The cross-section of thebeam is preferably perpendicular the emission or illumination vector,but can alternatively or additionally be parallel the emission orillumination vector, or be defined at any suitable angle relative tosaid vector. The emitted signal is preferably modified using emitteroptics (e.g., a focusing system, such as a set of mirrors or lenses),but can be otherwise modified.

The method can optionally include emitting one or more signals (and/orbeams, wherein the descriptions below for multiple signals can also beapplied to beams) from the emitter system. The multiple signals can bedirected in the same direction, in different directions, or in any othersuitable direction. The multiple signals can converge at a common pointexternal the sensing system, be directed toward different illuminatedscenes (e.g., within the same or different monitored regions), or beotherwise related. The multiple signals can be aligned in parallel, beperpendicular each other, or be otherwise arranged. When the multiplesignals are aligned in parallel, the multiple signals are preferablyaligned along the minor or auxiliary axis, but can alternatively bealigned along the major or monitoring axis or along any other suitableaxis. In one example, the multiple signals originate from the samepoint, and are directed in different directions separated bypredetermined angles. The multiple signals can have the same beamparameters (e.g., cross section, modulation frequency, modulation type,wavelength, amplitude, etc.), or different parameters. The multiplesignals (and/or beams) can be emitted: concurrently, serially (e.g., oneafter another, according to a predetermined schedule or other timeseries, etc.), at overlapping times, or at any suitable time.

In a first variation, emitting multiple signals (and/or beams) includescontrolling multiple emitters to emit the same or different signals(e.g., same modulation, same wavelength, same shape, same orientation,etc.). In a first embodiment, the multiple emitters can be separated bya predetermined distance (e.g., selected such that the signals do notinterfere or have minimal interference). Alternatively, or additionally,multiple emitters can be collocated. The multiple emitters can bearranged: proximate (e.g., separated by a distance, touching, etc.),distal, parallel (e.g., with active faces aligned along a common plane),proud, recessed, or otherwise arranged relative to each other. In asecond embodiment, the multiple emitters can be operated at differenttimes. Alternatively, or additionally, multiple emitters can be operatedat the same time. However, the multiple emitters can be otherwiseconfigured and operated.

In a second variation, emitting multiple signals (and/or beams) includessplitting a common emitted signal into multiple sub-signals. In oneembodiment, the signal is split prior to signal modification (e.g.,shaping, focusing, etc.), where each sub-signal can be individuallyfocused, directed, shaped, or otherwise modified to have the same ordifferent signal parameter values (e.g., which can be predetermined,dynamically determined, or otherwise determined). In a secondembodiment, the signal is split after signal focusing, where the focusedbeam is split into multiple discrete beams (e.g., by mirrors, lenses,etc.). In a third embodiment, the signal is split during signalfocusing, where the common signal can be split and focused at the sametime. In a specific example, emitting multiple signals includessplitting a common signal into three discrete beams, each separated by apredetermined separation angle. The three beams can be distributedvertically, such that the high beam is directed toward the primarysystem's head height, the low beam is directed toward the floor orsupport surface, and the central beam is directed straight ahead.However, the beams can be otherwise configured.

c. Recording the Reflected Signal at a Sensor

Sampling the reflected signal at a sensor S200 functions to recordreflections of the emitted signals (e.g., in beam form) off surfaces ofthe ambient environment, wherein the emitted signals strike surfaces inthe environment (e.g., object surfaces, structural surfaces, etc.) andis reflected back towards the system. The reflected signal is preferablysampled by a signal sensor, more preferably the detection system butalternatively any other suitable system, but can be otherwise recorded(e.g., sampled and stored), sampled, or otherwise measured.

The signal sensor (and/or resultant sample) preferably has a field ofview (FOV) with one or more larger dimensions than the beam, such thatthe signal sensor (and/or sample) samples (or represents) a physicalregion larger than the region receiving the incident signal (e.g., theilluminated scene region). The signal sensor and/or sample can beassociated with expected bright region(s) (corresponding to the portionsof the scene expected to reflect the beam), and expected dark region(s)(corresponding to non-illuminated portions of the scene, or portions ofthe scene that are not expected to reflect the beam). The locations anddimensions of expected bright and dark regions within the image orsensor are preferably predetermined (e.g., based on the detector systemposition relative to the emitter system position, determined duringcalibration, determined based on the relative beam angles, etc.), butcan alternatively or additionally be empirically determined (e.g., bethe regions with the highest frequency of having bright pixels) orotherwise determined. However, the signal sensor (and/or signal) FOV orother parameter thereof can be equal to, smaller than, or otherwiserelated to the beam dimensions.

The reflected signal can be sampled at a predetermined frequency (e.g.,the same frequency as signal emission, alternatively faster or slower),but can alternatively be performed at any other suitable frequency. Eachemitted signal can be sampled one or more times. The signal ispreferably sampled at a sampling time, wherein the sampling time can bea predetermined time duration after the signal and/or beam emissiontime; but can alternatively or additionally be sampled during apredetermined time window (e.g., from the emission time); becontinuously sampled, or otherwise sampled. The sampling time can be theemission time, be a predetermined duration after the emission time(e.g., based on the signal time of flight or round-trip duration to amonitored distance), or be any other suitable recordation time. Themonitored distance can be a minimum monitored distance, maximummonitored distance, expected surface distance, average monitoreddistance, or be any other suitable distance. In one variation, the samesignal can be sampled multiple times (e.g., during the same or differentexposure periods), wherein different sampling times can correspond todifferent physical distances from the sensing system. In this variation,the method can optionally include accounting for primary system motionbetween the emission and sampling time, between sequential samplingtimes, and/or during any other suitable timeframe. However, the signalcan be sampled at any other suitable time.

Sampling the signal S200 can include: sampling an image of the monitoredregion including the illuminated scene; measuring the signal modulatedparameter shift (e.g., phase shift, using a phase detector; amplitudeshift, using pixel intensity; etc.); or sampling any other suitableparameter of the reflected signal. Sampling the reflected signal canoptionally include: selectively opening and closing a built-in shutterat the same or similar frequency as signal emission, filtering outwavelengths excluded from the signal, focusing the reflected signal intothe signal sensor, or otherwise modifying the sampled signal. Samplingthe reflected signal can include: at a sampling time, operating thesensor for an exposure duration. The exposure duration can bepredetermined, dynamically determined based on the ambient light (e.g.,inversely related to the ambient light), or otherwise determined. Thesampled measurement can be from a single sampling time, be atime-averaged measurement, be a statistical summary of a time series ofmeasurements (e.g., change rate, standard deviation, etc.), or be anyother suitable measurement. One or more signal samples (e.g., images)can be recorded during the exposure duration, wherein the objectparameters can be extracted from or verified against the resultant timeseries. The receipt time can be the recordation time, a time during theexposure duration, or be any other suitable time.

In variants including multiple emitted signals (e.g., includingauxiliary signals), recording the signal can include recording thereflected signals from each emitted signal. Alternatively, the reflectedsignals from a subset of the emitted signals can be recorded. Recordingthe reflected signals can include: concurrently recording the reflectedsignals from different beams (e.g., concurrently or asynchronouslyemitted); asynchronously recording the reflected signals from differentbeams; or recording the reflected signals from different beams in anysuitable order. The reflected signals from different beams arepreferably recorded using a common detection system (e.g., signalsensor, detector sensor, image sensor, etc.), but can alternatively berecorded by different signal sensors (e.g., one for each signal; one foreach sampling time; etc.). In a specific example, recording reflectedsignals from different beams includes recording reflected signals fromall concurrently emitted beams at a common signal sensor, such that theresultant signal (e.g., image) includes measurements for each reflectedbeam. This signal can additionally or alternatively include signals forthe interstitial spaces between the beams, spaces around each beam(e.g., above, below each beam), or signals for any other suitablephysical region. Each beam can be associated with a predetermined set ofpixels, predetermined scene region (e.g., relative to the host system),and/or other spatial data. In one example, a horizontal main andauxiliary beam can be associated with a main pixel set and auxiliarypixel set, wherein the pixels within each set share a common polar angle(and/or are associated with a predetermined set of polar angles), andwherein the main pixel set and auxiliary pixel set are separated by apredetermined polar distance (specific example shown in FIG. 7).However, the reflected signals from different beams can be otherwiserecorded.

d. Determining a Surface Parameter Based on the Recorded Signal.

Determining a surface parameter based on the recorded signal S300functions to characterize the monitored region (e.g., ambientenvironment surrounding the primary system, the sensing system, etc.).The monitored region characterization can be used to generate scenemaps, navigation instructions (e.g., host system control instructions),or used in any other suitable manner. The monitored region can includesurfaces in the environment struck by the emitted beam, or be otherwisedefined. The surface parameters are preferably determined in real- ornear-real time, as the signals are sampled, but can additionally oralternatively be determined after a delay, in batches, after acharacterization event (e.g., an auxiliary sensor indicates that thereis an obstacle within the sensing system's line of sight), or at anysuitable time. The surface parameters can be determined by the on-boardprocessing system, the host processing system, a local computing system(e.g., device connected to a common local wireless network), a remotecomputing system (e.g., server system), or any other suitable system.

Determining the surface parameter S300 can include: determining pixelparameters for each of a set of pixels S320, and determining the surfaceparameter based on the pixel parameters S340. However, the surfaceparameter can be otherwise determined.

In variants with multiple emitted signals, the same or different surfaceparameter determination methods can be applied to samples for differentreflected signals. For example, a first method can be applied to a mainbeam, while a second method can be applied to the auxiliary beams (e.g.,based on the emitted beam parameters, the beam's spatial position,etc.).

Determining the pixel parameters S320 function to determine raw datafrom which scene characterizations can be extracted. The set of pixelscan be: pixels associated with expected illuminated scene regions (e.g.,bright scene regions), pixels associated with expected non-illuminatedscene regions (e.g., dark scene regions), pixels within an expectedpixel region (e.g., bright pixels within one or more expected brightregions, wherein the bright region can be a bright image region, brightpixel region, bright scene region, or other bright region; dark pixelswithin one or more expected dark regions wherein the dark region can bea dark image region, dark pixel region, dark or non-illuminated sceneregion, or other dark region), all bright pixels, all dark pixels,errant pixels (e.g., bright pixels within the expected dark region, darkpixels within the expected bright regions), all pixels, pixels having apredetermined set of indices, pixels corresponding to a detectedobstacle (e.g., previously detected using the sensing system, detectedusing an auxiliary sensor, etc.), adjacent pixels (e.g., pixels within agrid unit, a cluster, etc.), or any other suitable set of pixels. Theset of pixels used to determine the pixel parameters can be dynamicallydetermined, predetermined, or otherwise determined based on beamparameters, individual pixel parameters, noise parameters, or any othersuitable information.

In a first variation, pixels corresponding to a high-irradiance region(e.g., with a majority of the photon budget; main beam; etc.; imageregion, scene or ambient environment region, etc.) can be evaluated onan individual basis. In a second variation, pixels corresponding tolow-irradiance regions (e.g., less than a threshold irradiance orproportion of the photon budget; auxiliary beam; etc.; image region,scene or ambient environment region, etc.) can be aggregated (e.g.,binned or clustered together), wherein the resultant pixel value can beassigned to a larger region represented by the cluster. The aggregatedvalue can be a mean, median, weighted average, or other aggregatemeasure of the underlying pixels' parameters. The pixels can beclustered using: a grid or matrix, based on shared pixel parameters,based on anticipated shared surfaces (e.g., determined using anauxiliary range-finding system), or otherwise clustered. The clustershape, size, number, or other parameter can be predetermined,dynamically determined (e.g., based on the reflected signal strength,the signal-to-noise ratio, the detected distance, the illuminationpower, the incident surface angle, the ambient light, etc.), orotherwise determined. For example, a larger grid unit can be used whenthe estimated surface distance is further away, or when the illuminationpower for the beam is lower. However, the pixel set can be otherwiseselected.

The pixel can be a sensor pixel, an image pixel, or pixel of any othersuitable component or scene representation. Pixel parameters caninclude: signal phase; signal magnitude or intensity; modulation shift(e.g., phase shift, amplitude shift, etc.) and/or parameters thereof(e.g., amount, duration, etc.); color; wavelength; hue; saturation;pixel depth (e.g., represented distance); parallax shift; number,pattern, density, distribution, or other spatial characterization ofpixels having a shared parameter value; spatial characterization ofdifferent pixel groups (e.g., separation distance between groups ofbright pixels); classification (e.g., bright or dark pixel); or anyother suitable parameter. The pixel parameters can be sampled by thedetector sensor, calculated from the detector sensor signals, orotherwise determined. For example, the distance associated with eachpixel can be calculated from the modulation shift (example shown in FIG.9), the sampling time, and the emission time. However, the pixelparameters can be otherwise determined.

Determining the surface parameters based on the pixel parameters S340functions to characterize the scene's surfaces. The characterizedsurfaces are preferably those illuminated by the band, but canalternatively or additionally be secondary surfaces, such as thoseilluminated through multipathing effects. The surface parameters caninclude: surface presence, distance (e.g., relative to the sensingsystem), angular position relative to the system (e.g., azimuthal,polar, etc.), geometry (e.g., obstacle geometry, terrain), pose,kinematics, or any other suitable parameter. The surface parameters canbe determined based on the pixel parameters, the sensing system poserelative to the host system, the host system kinematics (e.g., location,velocity, acceleration, etc.), host system orientation, and/or any othersuitable parameter. The surface parameters can be calculated (e.g.,using a neural network, a rule set, etc.), selected, or otherwisedetermined.

When multiple beams are emitted, different surface (or object) parameterexpectations can be associated with each respective return signal. Forexample, the floor beam (e.g., cliff, low beam) can be associated withan expected object (e.g., floor) presence, the main beam (e.g., middlebeam) can be associated with no expected object presence, and theceiling beam (e.g., clothesline beam, high beam) can be associated withno expected object presence (e.g., surfaces too far away for the sensorto sample). In a specific example, the method can include: detecting anobstacle (e.g., object) in response to the range (e.g., external surfacedistance) for a pixel within the main pixel set falling below a distancethreshold; and detecting an obstacle (e.g., void) in response to therange for a pixel within the auxiliary pixel set (e.g., floor pixel set)exceeding a second distance threshold and/or not returning a signal. Themethod can optionally include emitting a second auxiliary beam, anddetecting an obstacle (e.g., an object) in response to the range for apixel within the second auxiliary pixel set (e.g., ceiling pixel set)falling below a distance threshold. The distance thresholds can be thesame for each beam, different (e.g., the main beam associated with alonger threshold, etc.), or otherwise related. The distance threshold(s)can be predetermined (e.g., static, set according to a predeterminedequation, etc.), dynamically determined, or otherwise determined. Thedistance thresholds can be determined based on the host system's(navigation) response time, host system orientation (e.g., tilt), hostsystem global location, host system location within a predetermined map,ambient environment parameters (e.g., ambient light), obstacles detectedin the scene, parameters of obstacle within the scene (e.g., size,shape, class, pose, position, etc.), or otherwise determined. However,each beam can be associated with a different expected object or surfaceparameter.

In a first example of surface parameter use, the method can include:detecting an obstacle within the illuminated scene and generatingnavigation instructions (e.g., to arrive at a predetermined endpoint orset of waypoints) to avoid the obstacle. The obstacle is preferably anunexpected feature in the monitored scene, but can be any other suitablefeature. The obstacle can be a physical object, a void, or be anysuitable obstacle. In a second example, the method can include:detecting the absence of an expected object (e.g., floor) within theilluminated scene (e.g., detecting a hole or void), and generatingnavigation instructions to avoid the regions lacking the expectedobject. In a third example, the method can include: determiningcharacteristics of the surface (e.g., angle relative to a gravity vectoror other reference vector, surface roughness, etc.) and generatingnavigation instructions based on the host system capabilities and thesurface characteristics (e.g., avoiding regions that the host system isincapable of traversing). However, the surface parameters can beotherwise used.

In a first variation, determining a surface parameter includes detectingthe presence of an object in the illuminated scene. Additionally oralternatively, determining the surface parameter can include: detectingthe absence of an object in the illuminated scene, wherein the object(e.g., floor) can be expected in the scene; detecting a void or hole inthe scene; or detecting the presence or absence of any other suitablescene feature (e.g., surface) within the illuminated scene. Detectingthe presence of an object in the illuminated scene can includeidentifying bright pixels in the resultant image, wherein bright pixelscan be associated with a diffusely reflective surface. Bright pixels canbe pixels with an intensity above a threshold intensity (e.g.,identified using a filter), pixel groups (e.g., multiple contiguouspixels) of pixels having an intensity above the threshold intensity,pixel groups having an average intensity above the threshold intensity,pixel sets having a modulation shift above a threshold value, pixel setswith parameter values differing from the neighboring pixels by athreshold amount, more or less than a threshold amount, or be otherwisecharacterized. Alternatively, the pixel parameter values (and/or surfaceparameter values) determined from one or more concurrently sampled beamreflections can be compared against an expected set of parameter valuesdetermined based on a predetermined scene topography, wherein an objectcan be detected when the sampled values differ from the expected values.However, the object presence (or absence) can be detected in any othersuitable manner.

In a second variation, determining a surface parameter includesdetermining the surface's angular position relative to the sensingsystem based on the recorded image. In one embodiment, a relativesurface position is determined based on the angular position associatedwith the pixels sampling the surface represented within the resultantimage. In an example, wherein the beam is directed with a major axisarranged horizontally, each lateral pixel position within the image isassociated with a different lateral angular position relative to thesensing system. For example, a bright pixel appearing in a far rightpixel in the image is indicative of an object to the right of thesensing system. In a second example in which the emitter system emits atop, middle, and bottom horizontal beam, the surfaces detected frombright pixels appearing in each expected bright region (e.g., brightband) can be mapped to: a predetermined altitude corresponding to thetop, middle, and bottom beams, respectively, and a predetermined lateralangular position (azimuthal angle) corresponding to the pixel's lateralposition within each band (example shown in FIG. 12). In a specificexample of the second example, the top and bottom beams can be weakerthan the middle beam, and be used to detect the “ceiling” (e.g., headheight) and floor topographies (e.g., detect an obstacle presence, suchas along the navigation route; floor absence, such as at the top of thestairs). However, the relative surface position can be determined in anyother suitable manner.

In a third variation, determining a surface parameter includesdetermining an object distance from the sensing system based on therecorded signal.

In a first embodiment, determining an object distance includesdetermining the modulation shift between the received signal and theemitted signal, and calculating the distance from the modulation shift(e.g., phase shift, amplitude shift). Determining the distance based onthe modulation shift can include using a predetermined shift-to-distancemap, calculating the distance based on the shift amount, or otherwisedetermining the distance.

In a second embodiment, determining an object distance includesmeasuring the reflectance duration (e.g., the difference between theemission time and the time of arrival) and calculating the distancebased on the reflectance duration and the signal speed (e.g., speed oflight).

In a third embodiment, determining an object distance includesdetermining the intensity of each pixel within the resultant image(e.g., the recorded signal), and determining the distance based on thepixel intensity (e.g., with different intensity values or rangescorresponding to different distances). Determining the distance based onthe pixel intensity can include using a predeterminedintensity-to-distance map, calculating the distance based on the pixelintensity, or otherwise determining the distance. The distancedetermination can additionally or alternatively be determined based onthe ambient light (e.g., as measured by the ambient light sensor), theexposure duration, the relative emission intensity or otherwisedetermined. For example, the determined distance can be increased as afunction of increasing ambient light or exposure duration.

When combined with the second variation, the third variation can resultin a range map, where the angular positions of points are determinedbased on the pixels and the range (distance) is determined based on thesignal return. In one example where a narrow beam is emitted, the pixels(or contiguous set thereof) in the bright band within the recordedimages can each be mapped to a predetermined angular position. Thedistances for each angular position can be determined based on the pixelintensity of the pixel associated with the respective angular position.In a specific example, the emitted beam spans 180°, and the angularpositions between 0° and 180° can be divided into ½° intervals. One ormore pixels can be assigned to each interval. This can result in avector of ranges. In one example, each position within the vector can beassociated with an interval position, and the value of the position canbe indicative of the object distance at the respective intervalposition. In a second example, the pixels can be associated withdirection vectors, and the range information can be combined with saiddirection vectors to create a point cloud for display or use by a hostor external system. However, the object distance can be otherwiserepresented and mapped.

In a fourth embodiment, determining an object distance includesdetermining the surface distance based on the beam emission angle andthe resultant pixel position of the reflected beam. For example, a beamemitted at a non-zero angle to the normal vector of the detection sensoractive surface can be treated as structured light, wherein the distancecan be determined from deviations from a predetermined reflected beamshape or pattern. In this embodiment, determining the distance caninclude: using a predetermined map correlating the shift distance, shiftpattern, or other shift parameter to a distance or distance adjustment;calculating the distance (e.g., using the distance adjustment) from areference distance for a reference pixel (e.g., wherein the referencedistance can be calculated based on a modulation shift, etc.); orotherwise determined. In a specific example, medial bright pixel shiftscan be associated with closer surfaces, while distal pixel shifts (e.g.,pixel shifts away from the image median) can be associated with furthersurfaces. However, the object distance can be determined in any othersuitable manner.

In a fourth variation, determining the surface parameter includesdetermining the surface material properties, wherein different materialproperties can be associated with different pixel parameter valuesand/or changes. The association between the material properties andpixel parameter values can be: predetermined, empirically determined,learned, or otherwise determined. In one embodiment, the surface colorcan be determined based on the wavelengths absorbed by the surface(e.g., emitted, but not reflected, wavelengths). In a second embodiment,the surface reflectivity can be determined based on the intensity changebetween the emitted and reflected signal. In a third embodiment, thesurface reflectivity can be determined based on bright pixel shift(e.g., errant bright pixels appearing in an expected dark region of thesampled signal, pixels associated with errant illuminated regionsdetected in the virtual scene representation, etc.). The shift pattern,distance, or other parameter thereof can be associated with differentmaterials and/or effects. In a first example, a shift pattern associatedwith diffuse reflections (e.g., scattered bright pixels) can beassociated with multipath effects, and ignored, associated with diffusesurfaces, used to correct the surface parameters determined using brightpixels in the expected bright region, or otherwise used. In a secondexample, a consistently shifted block of bright pixels can be associatedwith a smooth, specular reflection (e.g., glass). However, the surfacematerial properties can be otherwise determined.

In a fifth variation, determining a surface parameter includesdetermining the terrain of a plane based on the recorded signal. Thiscan function to monitor the auxiliary or minor axis of the scene (e.g.,vertical axis, horizontal axis, etc.). This can be particularly usefulwhen the primary system is moving through the monitored volume and/orwhen the signal strikes the plane at a non-normal angle. In one example(specific example shown in FIG. 18), determining the terrain of a planecan include: determining the range information and altitude for each ofa set of pixels within a resultant image, assigning a firstclassification (e.g., “low” or “cliff”) to the pixels having altitudesbelow a first threshold altitude and assigning a second classification(e.g., “high” or “raised”) to pixels having altitudes above a secondthreshold altitude. The altitude for each pixel can be determined basedon the angular pixel vectors and a ground surface normal vector orgravity vector determined by an accelerometer, another sensor, simply byfiat, and/or otherwise determined. In a specific example, the floor canbe defined by a plane fit to points that fall into the floor region(optionally rejecting outliers) and the altitude defined as a normaldistance to that floor plane. However, the pixel altitude can beotherwise determined. The example can additionally or alternativelyinclude assigning a “floor” classification to pixels with altitudesfalling between the first and second thresholds, pixels with altitudesfalling within a predetermined range of a given altitude, or pixelssatisfying any other suitable condition. The example can additionally oralternatively include assigning an “unknown” classification to pixelswith altitudes falling on the border of different altitude ranges,pixels with unknown altitudes, pixels that seem anomalous based onadjacent pixel values, or any other suitable pixel. In a specificexample, this can result in a terrain or altitude map (e.g., of thefloor) with a classification for each unit region of the plane, a subsetof the plane regions, a virtual object representation within the virtualscene representation (e.g., obstacle points), or for any suitable set ofphysical regions, virtual regions, or pixel regions.

In a second specific example, the floor can be defined by identifying afirst return signal (e.g., pixel associated with the shortest range)within a set of pixels associated with a floor beam and setting therange extracted from the first return signal as the floor height ordistance from the system. Additionally or alternatively, the firstreturn signal can be the signal corresponding to the shortest range thatis within a predetermined confidence interval of an estimated floordistance. The estimated floor distance can be: empirically determined,predetermined (e.g., based on the host system height or system placementon the host system), dynamically determined (e.g., based on system orhost system tilt, as sampled by on-board sensors), or otherwisedetermined. However, the first return signal can be otherwisedetermined. The pixels associated with floor beam can be pixels within apredetermined image region, pixels associated with a predeterminedangular position (e.g., predetermined set of polar angles, etc.), or beany suitable set of pixels. The floor can be represented in the virtualscene representation as a plane arranged the floor distance away fromthe system, wherein the angular orientation of the floor relative to thehost system can be determined by fiat, determined based on the hostsystem (e.g., based on host system tilt, as sampled by host systemorientation sensors), or otherwise determined. Obstacles can be detected(from the pixels associated with the floor beam) as surfaces with aheight (e.g., z height) higher than the floor height. In one variation,this includes: determining a scene range for each pixel in the set,mapping the scene ranges to a virtual scene representation based on thescene position associated with the respective pixel, and determiningobstacles as surfaces above the virtual floor based on the virtual scenerepresentation. However, obstacles can be otherwise determined.Alternatively or additionally, voids (e.g., cliffs, steps, etc.) can bedetected as missing surfaces or surfaces with a height less than thefloor height. However, the floor can be otherwise determined.

In a sixth variation, determining the surface parameter includesdetermining object parameters. Object parameters can include: an objectidentity (e.g., class, subclass, etc.), object geometry, object pose, orany other suitable parameter. In one embodiment, the surface parametersdetermined from one or more concurrently sampled beam reflections can beused to generate a virtual scene representation, wherein objects can bedetected from the virtual scene representation using pattern matching(e.g., matching a predetermined object geometry to the virtual sceneslices), histograms (e.g., by calculating a histogram of gradients andmatching the gradient vectors to a predetermined set of vectors), orotherwise determined. In a second embodiment, each pixel can beassociated with a distance-based area map that correlates the scenefootprint represented by a pixel for each of a set of distances. In thisvariation, the method can include: identifying the object pixelsassociated with the obstacle, determining the pixel distance for eachobject pixel, determining the area for each object pixel based on thearea map and respective pixel distance, and calculating the obstaclesize based on the areas collectively represented by the object pixels.However, the object parameters can be otherwise determined.

In an example of the method, the method can include: emitting a first,second, and third beam from a common emission point; recording ameasurement (e.g., image) encompassing reflected signals from the first,second, and third beams; and determining the obstacles in threedifferent physical regions corresponding to the first, second, and thirdbeam directions, respectively. In a specific example, the first beam canbe a high beam, the third beam can be a low beam, and the second beamcan be a center beam. The recorded image can include a high, middle, andlow band corresponding to the high, center, and low beams. The ceilingor head-height terrain can be determined from the high band, the flooror cliff-height terrain can be determined from the low band, andobstacles in the traversal path can be determined from the middle band.However, the method can be otherwise performed.

The method can optionally include identifying transparent, reflectivesurfaces S400, such as glass, from the recorded signal. Identifyingtransparent surfaces can function to identify the presence of thetransparent surface, the location of the transparent surface, thedistance of the transparent surface, the type of transparent surface(e.g., based on the reflection pattern), the shape of the transparentobject, or any other suitable parameter of the transparent surface.Identifying transparent surfaces includes: identifying errant regionsand detecting the transparent surface presence based on the parametersof the errant regions. However, the transparent surfaces can beotherwise detected.

Identifying errant regions preferably includes identifying brightregions deviating from an expected bright region or pattern (e.g.,detecting the bright regions in an expected dark regions), but canalternatively include identifying bright regions within an expected darkregion, identifying dark regions deviating from an expected dark region,or otherwise identified. The regions can be: pixel regions (e.g., imagepixels or sensor pixels), scene regions, or any other suitable region.The expected bright region pattern is preferably the regions from which(or pixels at which) the reflected signal is expected to be received,but can be otherwise defined. When the expected bright region is anexpected bright scene region, the expected bright scene region can be ascene region within the virtual scene representation associated withsignal return. The expected bright scene region can be: empiricallydetermined (e.g., using calibration, historic signals, etc.), apredetermined region in the virtual scene representation (e.g., based onthe system position on the host system, the beam parameters such as beamdimension, etc.), pre-associated with the host system (e.g., be apredefined bright region within the host system's coordinate system), orotherwise determined. When the expected bright region is an expectedbright pixel region, the expected bright pixel region can have one ormore pixels along the auxiliary axis (e.g., along the minor axis, inheight, etc.), multiple pixels along the monitoring axis (e.g., alongthe major axis, in width, etc.), or have any suitable dimension. Theexpected bright region pattern (e.g., band pattern) can be predetermined(e.g., based on the beam parameters, such as beam dimensions, phase,modulation, etc.), dynamically determined (e.g., based on triangulationor sensing system or primary system tilt), determined based on asecondary band from a secondary beam (e.g., indicative of objectpresence), or otherwise determined. However, errant pixels can beotherwise identified.

In a first variation, detecting the transparent surface includesidentifying errant pixels (e.g., determining a bright pixel in anexpected dark pixel region, detecting a band shift from an expectedpixel position).

In a second variation (example shown in FIG. 13), detecting thetransparent surface presence includes identifying a consistent shift inerrant pixels (e.g., wherein a threshold number of errant pixels, orerrant pixel population, is shifted by a consistent pixel distance,phase, etc.).

In a third variation, detecting the transparent surface presenceincludes identifying a population of errant pixels, wherein thepopulation satisfies a predetermined population condition (example shownin FIG. 14). The predetermined population condition can include:matching a predetermined pattern (e.g., wherein the errant pixelpopulation substantially matches the pattern, which can bemachine-learned, associated with a modulation pattern or phase, orotherwise determined), having a predetermined number of pixels, having apredetermined concentration of pixels, having an average or medianintensity above a threshold intensity, or satisfying any other suitablecondition.

In a fourth variation, detecting the transparent surface includesdetermining an object or obstacle position from a first band,determining an expected band parameter (e.g., intensity, position,sharpness, etc.) for a second band based on the determined obstacleposition, comparing the expected band parameter to the actual bandparameter, and detecting a transparent surface in response to a bandparameter deviation between the actual and expected bands. However, atransparent surface can be otherwise determined.

In a fifth variation, detecting the transparent surface includes:identifying errant pixels, detecting a reflective surface (e.g.,specular reflective surface) based on the errant pixels, and detectingno object from a corresponding set of pixels within the expected brightpixel region (e.g., detecting a distance beyond a predeterminedthreshold, the corresponding set of pixels' distances are substantiallysimilar to other pixels' distances within the expected bright pixelregion, etc.); example shown in FIG. 15. The corresponding set of pixelscan be pixels within the expected bright pixel region that are alignedwith the errant pixels (e.g., vertically aligned, horizontally aligned,etc.), or be any other suitable set of pixels. However, the transparentobject can be otherwise determined.

The method can optionally include generating a virtual representation ofthe scene (e.g., a scene map) S500. The virtual representation ispreferably generated based on the scene parameters per pixel, but canadditionally or alternatively be generated based on the host systemkinematics, host system pose (e.g., orientation, location, etc. relativeto the scene), or any other suitable information. In one variation, thesurface parameters (e.g., surface distances) determined from each pixelis mapped to the spatial position corresponding to the respective pixelto generate a vector cloud or point cloud. In this variation, the methodcan optionally include incrementally mapping a physical space as thehost system moves the sensing system relative to the space (e.g.,wherein the point cloud or other virtual representation of the scene canbe generated slice-by-slice; example shown in FIG. 16) or relative tothe space (e.g., as the host system rotates; example shown in FIG. 17).Each local virtual representation (e.g., slice, determined using thesensing system) can be mapped to a global virtual representation of thescene. For example, the location of the local virtual representationwithin the global virtual representation can be determined based on thehost system location (e.g., using a GPS system, indoor location system,other location system, etc.), host system kinematics (e.g., usingodometry to track the sampling location relative to a referencelocation), or otherwise determined. In a second example, generating theglobal representation can include generating a coordinate transformbased on the host system orientation (e.g., pitch, yaw, roll) thattransforms the host system coordinates and/or sensing system coordinatesto global coordinates, and transforming the virtual scene representationbased on the coordinate transform. In a specific example, the methodincludes generating a series of virtual scene representations using themethod, and stitching the virtual scene representations together basedon the host system movements (e.g., as determined from on-board sensors,host system control instructions, etc.). However, the virtual scenerepresentation can be otherwise generated.

The method can additionally or alternatively include calibrating thesensing system. The calibration is preferably performed in-situ (e.g.,in-field), but can alternatively be performed when the primary system isin a standby state or at any other suitable time. The calibration ispreferably performed in real- or near-real time (e.g., for each signalmeasurement), but can be performed at any other suitable frequency. Thecalibration is preferably performed automatically, but can alternativelybe performed manually, teleoperatively (e.g., wherein the calibration isperformed by or at a remote computing system and sent to the sensingsystem), or performed by any other suitable system. The sensing systemcan be calibrated using the recorded signal for a single beam (e.g., thedark pixels and bright pixels for a single beam; etc.), the recordedsignals for multiple beams (e.g., using the signal from a first beam asa reference point for a second beam), the expected dark pixel and brightpixel locations for a beam, a series of reflected signal measurementsrecorded over time (e.g., calibrated or verified using the beamparameter changes over time, etc.), the signals recorded by a secondaryrangefinding system, or calibrated using any other suitable set ofinformation. Calibrating the sensing system can include: correcting formultipath errors, correcting for ambient light (e.g., using ambientlight measurements), correcting for signal interference, or correctingfor any other suitable error.

In a first variation, calibrating the sensing system can include:identifying errant bright regions in the expected dark regions anddynamically correcting for multipath interference based on the errantbright regions. In a first embodiment, the errant bright regions areilluminated scene regions, detected from pixel signals, located withinexpected non-illuminated scene regions. In this embodiment, the pixelsignals can be converted to a virtual scene representation, wherein thevirtual scene representation can be associated with expected illuminatedregions and expected non-illuminated regions. The expected illuminatedand non-illuminated regions can be determined based on the emitted beampose (e.g., position and/or orientation) relative to a reference frame(e.g., a global coordinate system, host system coordinate system, etc.),the emission parameters (e.g., emission intensity, angle, etc.), orotherwise determined. In a second embodiment, the errant bright regionsare bright pixel regions detected in expected dark pixel regions withinthe image recorded by the sensor. However, the expected bright and darkregions can be any suitable region.

In a first embodiment, dynamically correcting for multipath interferencecan include: subtracting, ignoring, discounting, filtering, correcting(e.g., using sparse reflection analysis, random forest trainingalgorithms, iteratively optimized, etc.), or otherwise processing theimage to remove the errant bright pixels from the expected dark pixelregion and/or ignore the distance signals from the errant bright pixels(example shown in FIG. 14). In a second embodiment, dynamicallycorrecting for multipath interference can include determining theintensity of the errant bright pixels (e.g., average intensity, etc.)and subtracting the errant bright pixel intensity from the bright pixels(in the expected pixel positions) prior to distance determination.However, the sensing system can otherwise calibrate for multipath errorsbased on the expected dark pixel and/or bright pixel positions.

In a second variation, calibrating the sensing system can include:identifying the edges of a band, identifying bright pixels outside ofthe band edges (e.g., scatter, halo) as errant bright pixels, removingthe errant bright pixels from the image (e.g., to correct for multipatherrors), and determining the object distance based on the processedimage.

In a third variation, calibrating the sensing system can include:recording a primary measurement for a monitored region using the sensingsystem, recording a secondary measurement for the same monitored regionusing a secondary range-finding system, and calibrating the sensingsystem based on the secondary measurement. In a first embodiment,calibrating the sensing system based on the secondary measurement caninclude identifying a common sub-region or object shared between theprimary measurement and secondary measurement and iteratively adjustinga parameter of the sensing system until the object distance derived fromthe primary measurement substantially matches the object distancederived from the secondary measurement. The common sub-region or objectcan be determined using dead reckoning (e.g., wherein the relativepositions of the sensing system and secondary range-finding system arefixed and known; wherein pixels of the sensing system are pre-mapped topixels of the secondary range-finding system, etc.), using objectrecognition (e.g., wherein the same object or feature are recognized inboth measurements), or otherwise determined. However, the sensing systemcan be otherwise calibrated.

The method can additionally or alternatively include calibrating thesecondary range-finding system using sensing system measurements. In onevariation, this can include: recording a primary measurement for amonitored region using the sensing system, recording a secondarymeasurement for the same monitored region using a secondaryrange-finding system, and iteratively adjusting the secondaryrange-finding system parameters until the pattern of measured distancessubstantially match (e.g., within a predetermined range of error).However, the secondary range-finding system can be otherwise calibrated.

Embodiments of the system and/or method can include every combinationand permutation of the various system components and the various methodprocesses, wherein the method processes can be performed in any suitableorder, sequentially or concurrently.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the preferred embodiments of the invention withoutdeparting from the scope of this invention defined in the followingclaims.

We claim:
 1. An obstacle detection method, comprising: emitting sourcelight; shaping more than a threshold proportion of the source light intoa narrow light beam having a minor dimension; illuminating an ambientenvironment with the narrow light beam; sampling, at an optical sensorwith a field of view larger than the minor dimension, a reflection ofthe narrow light beam off the ambient environment, wherein the opticalsensor is associated with an expected bright region corresponding to anexpected reflection of the narrow light beam and an expected dark regioncorresponding to a non-illuminated region; and determining an externalobstacle parameter, for an external obstacle in the ambient environment,based on pixel parameters of a first bright pixel detected within sensorpixels associated with the expected bright region.
 2. The method ofclaim 1, wherein the minor dimension extends along an auxiliary axis,the method further comprising monitoring the auxiliary axis with anauxiliary light beam.
 3. The method of claim 2, wherein the minordimension comprises a beam height of the narrow light beam, the methodfurther comprising splitting the source light into the narrow light beamand the auxiliary light beam, the auxiliary light beam comprising aminority of the source light, wherein the main light beam and auxiliarylight beam are associated with the expected bright region and anauxiliary expected bright region, respectively.
 4. The method of claim3, wherein the source light comprises infrared light and is emitted withan average optical power of 2 W or less.
 5. The method of claim 3,further comprising detecting a second object based on aggregatedparameter values of adjacent bright pixels detected within sensor pixelsassociated with the auxiliary expected bright region.
 6. The method ofclaim 3, wherein the auxiliary light beam is separated from the mainlight beam by an emission angle.
 7. The method of claim 6, furthercomprising splitting a second subset of the source light into a secondauxiliary light beam, the second auxiliary light beam emitted at asecond emission angle substantially equal to and opposite from theemission angle.
 8. The method of claim 7, wherein the auxiliary lightbeam and second auxiliary light beam are emitted at opposing emissionangles defined along a vertical axis aligned along the minor dimension,wherein the auxiliary light beam is associated with a high verticalposition, the main light beam is associated with a middle verticalposition, and the second auxiliary light beam is associated with a lowvertical position.
 9. The method of claim 8: wherein the main light beamis associated with a main pixel set, the auxiliary light beam isassociated with an auxiliary pixel set, and the second auxiliary lightbeam is associated with a second auxiliary pixel set, wherein the mainpixel set, the auxiliary pixel set are concurrently sampled by theoptical sensor; wherein the external obstacle parameter comprises anobstacle presence, wherein determining the external obstacle parametercomprises: detecting an object presence in response to an externalsurface distance, determined based on the pixel parameters of the firstbright pixel, falling below a distance threshold; the method furthercomprising: detecting a void in response to a second external surfacedistance, determined from a second bright pixel within the auxiliarypixel set, exceeding a second distance threshold; and detecting presenceof a second object in response to a third external surface distance,determined from a third bright pixel within the second auxiliary pixelset, exceeding a third distance threshold.
 10. The method of claim 1,wherein the obstacle parameter comprises an obstacle distance, whereinthe light comprises phase-modulated light, wherein the obstacle distanceis determined based on a phase shift in reflected light.
 11. The methodof claim 10, further comprising determining an angular position of theobject relative to the optical sensor based on a pixel position of thefirst bright pixel.